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  2. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: . Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.

  3. Artificial intelligence in fraud detection - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    Higher levels of fraud detection entail the use of professional judgement to interpret data. Supporters of artificial intelligence being used in financial audits have claimed that increased risks from instances of higher data interpretation can be minimized through such technologies. [ 12 ]

  4. List of tools for static code analysis - Wikipedia

    en.wikipedia.org/wiki/List_of_tools_for_static...

    Clang – The free Clang project includes a static analyzer. As of version 3.2, this analyzer is included in Xcode. [14] Infer – Developed by an engineering team at Facebook with open-source contributors. Targets null pointers, leaks, API usage and other lint checks. Available as open source on github. Understand

  5. Google hacking - Wikipedia

    en.wikipedia.org/wiki/Google_hacking

    The concept of "Google hacking" dates back to August 2002, when Chris Sullo included the "nikto_google.plugin" in the 1.20 release of the Nikto vulnerability scanner. [4] In December 2002 Johnny Long began to collect Google search queries that uncovered vulnerable systems and/or sensitive information disclosures – labeling them googleDorks.

  6. Web scraping - Wikipedia

    en.wikipedia.org/wiki/Web_scraping

    Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.

  7. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  8. Server-side request forgery - Wikipedia

    en.wikipedia.org/wiki/Server-side_request_forgery

    Server-side request forgery (SSRF) is a type of computer security exploit where an attacker abuses the functionality of a server causing it to access or manipulate information in the realm of that server that would otherwise not be directly accessible to the attacker.

  9. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge from that data to solve problems in other application domains.